Explore the concept of Ollivier Ricci curvature and its applications in network analysis through this 56-minute lecture from the Applied Algebraic Topology Network. Delve into the origins of this geometric notion and its adaptation to discrete structures like directed hypergraphs. Learn how optimal transport problems and Wasserstein distance contribute to defining this edge-based measure, and discover its effectiveness in detecting clustering and sparsity in network structures. Examine the implementation of Ollivier Ricci curvature in analyzing chemical reaction networks, and gain insights into metric measure spaces, undirected and directed graphs, and the properties of directed hypergraphs. Investigate the classification of directed hypergraphs, explore background in network analysis, and understand the significance of Ricci curvature in this context. Conclude with an examination of hyperloops, real network analysis, and random network analysis, followed by a Q&A session and summary.